Obtaining Information from Different Devices in a Computer Network

ABSTRACT

Illustrative embodiments of the invention provide for obtaining information from different devices in a computer network. Data representing the information from each of the different devices is received, the data is in a specific form relating to each of the different devices. The data from each of the different devices is assigned to one or more entities as defined by an information model. The data from each of the different devices is grouped using an adaptation layer before assigning the data from that device to one or more entities.

PRIORITY

The present application is a divisional application of U.S. patentapplication Ser. No. 10/662,038, Attorney Docket No. CNTW-021/01US,“System and Method for Mapping Between and Controlling Different DeviceAbstractions,” filed on Sep. 12, 2003; which claims the benefit of U.S.Provisional Patent Application No. 60/410,707, Attorney Docket No.CNTW-021/00US, “System and Method for Mapping Between and ControllingDifferent Device Abstractions,” filed on Sep. 13, 2002; each of which isincorporated herein by reference in its entirety for all purposes.

RELATED APPLICATIONS

The present application is related to the following commonly-owned U.S.patent applications:

Ser. No. 09/942,834, entitled System and Method for Generating aConfiguration Schema, filed Aug. 29, 2001;

Ser. No. 09/942,833, entitled System and Method for Modeling a NetworkDevice's Configuration, filed Aug. 29, 2001;

Ser. No. 10/145,868, entitled System and Method for TransformingConfiguration Commands, filed May 15, 2002;

Ser. No. 10/617,420, entitled Repository-Independent System and Methodfor Asset Management and Reconciliation, filed Jul. 10, 2003; and

Ser. No. 10/213,958, entitled System and Method for EnablingDirectory-Enabled Networking, filed Aug. 7, 2002;

all of which are incorporated herein by reference in their entirety forall purposes.

FIELD OF THE INVENTION

The present invention relates to configuring and managing networkedcommunication systems. In particular, but not by way of limitation, thepresent invention relates to systems and methods for using aninformation model to map between normalized representations of differentnetwork resources having different features.

BACKGROUND OF THE INVENTION

Networking architectures and network devices, such as routers andswitches, as well as their configurations, are becoming increasinglycomplex both in structure and functionality. Such complexities requirenetwork engineers or other personnel to know hundreds or thousands ofvendor-specific command or syntaxes and to master both the hardware andsoftware idiosyncrasies of each differently manufactured networkeddevice in order to successfully configure and manage a network. Buttraditional network management techniques, which include network deviceconfiguration and maintenance processes, fail to amply provide networkadministrators (or any network user) with a means to control thecreation, the deployment, or the modification of each deviceconfiguration in a scalable and consistent manner.

Rather, network operators often configure devices without regard to anyof the business processes affected by implemented configurations, whichcan lead to a disruption of network services. Without any mechanism fortying business processes and network management processes together, anewly applied configuration to a device just becomes a mere setting on adevice. Consequently, the entire functionality of the configured deviceis not performed with business considerations prior to or after thisconfiguration, which in turn, isolates the network processes from anorganization's business processes. This hinders network efficiency. Asmost existing networking tools (e.g., provisioning tools) do not offer aview of the entire network, they typically offer only a limited viewinto, for example, an individual interface of a device.

The combined increase in network users and in sophistication ofnetworked applications further militates integrating network managementand business processes by establishing business rules that govern theusage of shared network resources. For example, a set of business rulescan determine which user or network traffic has priority in using thoseshared network resources. But to control networking processes, eachnetwork resource's structure and functionality should be normalized toshare and to reuse application data.

To normalize the structure and functionality of each network resourcerequires at least abstracting the resource's functionality. Butabstracting resource functionality is difficult because most networksare built using different devices, each of which have many differentcapabilities and command syntaxes. Further, different vendors usedifferent programming models for their vendor-specific network devices.The use of different programming models often leads to an inoperable orsuboptimal networking of resources. For example, the use of variedprogramming models tends to impair a network operator's ability todetermine whether a certain traffic conditioning used to separatedifferent classes of traffic is correct.

FIG. 1 is a diagram showing network resources as sources of networkinformation, each of which is associated with a different programmingmodel. For example, a network portion 100 includes a first routermanufactured by vendor one having a set of vendor-specific command lineinterface (“CIA”) commands 102, a second router built by vendor twohaving another set of vendor-specific CIA commands 104, and one or morerepositories of one or more Policy Information Bases (“PIBs”) and/orManagement Information Bases (“MIBs”) 106. If FIG. 1 represents aportion of a conventional network, some routers support CLI 102 and 104for provisioning while other routers employ Simple Network ManagementProtocol (“SNMP”) for monitoring, which includes information from MIBsand PIBs 106.

Without an underlying uniform data representation 110 that relates theCLI commands to SNMP commands, it is in general impossible to correlatethe commands of one programming model to the commands of anotherprogramming model. And since many network vendors build separateapplications for managing different sets of features present in the samevendor-specific device, a minimum number of multiple applications arerequired to manage and to provision devices from not only differentdevices from different vendors, but also from the same vendor as well.An example of an instance where multiple applications are necessary isthe case where two or more billing applications collect data differentlyand use different metrics to determine an amount that a network customershould be billed. This determination is complicated further if there aredifferent devices supporting different proprietary MIBs to generatedata, which are typically not in a suitable form for the billingapplications to process.

Although present devices and techniques for managing networks arefunctional, they are not sufficiently accurate or otherwisesatisfactory. Accordingly, a system and method are needed to address theshortfalls of present technology and to provide other new and innovativefeatures.

SUMMARY OF THE INVENTION

Exemplary embodiments of the present invention that are shown in thedrawings are summarized below. These and other embodiments are morefully described in the Detailed Description section. It is to beunderstood, however, that there is no intention to limit the inventionto the forms described in this Summary of the Invention, in theAbstract, or in the Detailed Description. One skilled in the art canrecognize that there are numerous modifications, equivalents, andalternative constructions that fall within the spirit and scope of theinvention as expressed in the claims.

The present invention provides, among other things, a computerizedmethod for managing a computer network, comprising forming a firstrepresentation of a network clement as a physical entity in aninformation model, the first representation having a form independent ofan implementation defined by a vendor; and mapping a portion of thefirst representation from the information model to a secondrepresentation in a vendor-independent data model residing in a firstrepository, the second representation having a form suitable for usewith the first repository.

Another exemplary embodiment is a computerized method for obtaininginformation from different devices in a computer network, comprisingreceiving data representing the information from each of the differentdevices, wherein the data is in a specific form relating to each of thedifferent devices; assigning the data from each of the different devicesto one or more entities as defined by an information model; and groupingthe data from each of the different devices using an adaptation layerbefore assigning the data from that device to one or more entities.

Another exemplary embodiment is a system for managing a computernetwork, comprising a processor; and a memory containing a plurality ofprogram instructions configured to cause the processor to form a firstrepresentation of a network clement as a physical entity in aninformation model, the first representation having a form independent ofan implementation defined by a vendor; and map a portion of the firstrepresentation from the information model to a second representation ina vendor-independent data model residing in a first repository, thesecond representation having a form suitable for use with the firstrepository.

Yet another exemplary embodiment is a system for obtaining informationfrom different devices in a computer network, comprising: a processor; amemory containing a plurality of program instructions configured tocause the processor to receive data representing the information fromeach of the different devices, wherein the data is in a specific formrelating to each of the different devices; assign the data from each ofthe different devices to one or more entities as defined by aninformation model; and group the data from each of the different devicesusing an adaptation layer before assigning the data from that device toone or more entities.

These and other exemplary embodiments are described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

Various objects and advantages and a more complete understanding of thepresent invention are apparent and more readily appreciated by referenceto the following Detailed Description and to the appended claims whentaken in conjunction with the accompanying Drawings wherein:

FIG. 1 is a diagram showing network resources as different sources ofnetwork information;

FIG. 2 illustrates an exemplary managed entity in accordance with anembodiment of the present invention;

FIG. 3 is an exemplary managed entity representing a router inaccordance with one embodiment of the present invention;

FIG. 4 illustrates one method of performing mapping translations usingan exemplary information model in accordance with one embodiment of thepresent invention;

FIG. 5A is an exemplary information model represented as a layeredinformation model according to one embodiment of the present invention;

FIG. 5B is another representation of the exemplary information model ofFIG. 5A, according to a specific embodiment of the present invention;

FIG. 6 illustrates a system for using an exemplary information model tofacilitate the collection, correlation, and integration of differenttypes of information according to one embodiment of the presentinvention; and

FIG. 7 is an exemplary model for representing a user according to oneembodiment of the present invention.

DETAILED DESCRIPTION

The present invention provides a system and a method for managingnetworks including one or more different devices having differentcommand syntaxes, different programming models, and/or differentfunctionalities. An exemplary system and method enables differentnetwork applications to share and exchange data for provisioning andmanaging network elements, for example. Among other things, the presentinvention facilitates the sharing and exchanging of data by using anormalized representation of network resources to, for example, maphardware and/or software features associated with at least one device toother hardware and/or software features of other, different devices. Thenormalized representations further enable similar functions in differentdevices to be equated regardless of having dissimilar hardware and/orsoftware features, such as dissimilar command structures andimplementations. Network resources generally include any network device,application, person, role, or any other element associated with aparticular network.

The present invention provides an information model for representingdifferent devices, including different programming models and/ordifferent functionalities, as a common representation or abstraction,according to at least one embodiment of the present invention. Inparticular, different hardware features of a network device arenormalized for representing the physical composition of dissimilardevices in a common way, such as by a data model, which enables mappingof equivalent physical capabilities of different devices. Further, byrepresenting one or More physical characteristics of a device as, forexample, an extensible representation of the physical characteristics(e.g., represented in XML), the associated logical functions of thatdevice can also be related to logical functions of other differentdevices.

As described herein, an “information model” can refer to entities in amanaged environment (“managed entities”) that constitute a network, theinterrelationships and behavior of such managed entities, and/or howdata flows within the network in a manner that is independent of how thedata is stored and retrieved in a repository. An information modeltherefore can include abstractions and can represent the variousentities in a managed environment. Further, the information model can beused as a “dictionary” that defines different characteristics of managedentities and how those characteristics relate to each other. Forexample, an information model can be a data structure for organizingphysical and logical information for describing the physical and logicalcharacteristics of managed entities. This data structure can also beused to describe how other managed entities use and are related tospecific physical and logical managed assets. By using an exemplaryinformation model of the present invention, different networkingproducts and applications can share and reuse information with whichmanaged entities relate.

A “managed entity” can refer to any physical or logical entity that canbe managed by a network operator, but need not represent only managednetwork devices. For example, a managed entity can also refer torouters, interfaces, routes, users, roles (e.g., as customer),applications, configuration settings, policies, statistics or to anyother entity that directly or indirectly affects operation of a networkdevice.

A “data model” can refer to any concrete representation of theinformation model that defines how data is stored, manipulated and/orretrieved using a specific type of repository and access protocol. Adata model, which can include data structures, operations, rules, andthe like, is analogous to the implementation of the data defined in aninformation model, but in a particular repository. “Mapping,” asdescribed herein can refer to model mapping, which is a translation fromone type of model (e.g., data model) to another type of model. Modelmapping changes the representation and/or level of abstraction used inone model to another representation and/or level of abstraction inanother model. Model mapping can refer to a mapping from an informationmodel to a data model. This type of mapping is usually exemplifiedthrough the mapping to a standards-based data model (i.e., a data modelwhose constructs are based on data structures and protocol elementsdefined in a standard). Model mapping can also refer to a mappingbetween different data models. This type of mapping is typified byoptimizing a standards-based data model in order to take advantage ofthe features of a particular vendor implementation.

Further describing an embodiment of the present invention, differentsoftware features (e.g., traffic conditioning, etc.) that areimplemented using different functions (e.g., different queuingalgorithms, etc.) can also be normalized for representing logicalcharacteristics in a common way, such as a single model. Such a commonrepresentation enables mapping of the same or equivalent functionalitysupported by two devices even though the mechanisms by which thatfunctionality is supported are different. By representing logicalcharacteristics in a common way, those different devices requiring acombination of commands to effectuate functionality in a manner similarto other devices requiring only a single command for performing asimilar functionality. With a common representation, it becomes possibleto coordinate the different commands of different devices to provide acommon service.

According to a specific embodiment, different software features can bemapped onto different hardware to enable a network operator to design anetwork architecture that is independent of any one vendor's hardwareand/or software implementation. Consequently, one or more hardwareand/or software features, as “managed entities” of network devices, canbe enabled or disabled through software regardless to whether anadministrative model is different than a corresponding programmingmodel. Thus, the administrative capabilities of a device can beabstracted into a common representation, so that the functionality ofdifferent devices can be managed and coordinated concurrently inaccordance with business processes as defined, for example, by businessrules.

Further to the present invention, some embodiments provide an exemplaryinformation model that enables business rules to be translated into formthat can be used to define network services, such as deviceconfiguration commands. Business rules can refer to one or moreconstraints using, configuring, monitoring and/or managing networkdevices, such as by the type of user, the time of day a service isrequested, the users authorized to implement a network configuration,etc. Notably, some device command syntaxes and programming models fordevice configuration may not be suitable for integration with businessrules.

An exemplary information model can also be used with a set of policiesto be integrated with the representations of the business rules and theother managed entities according to the present invention. The policiesare defined, and represented, at a different level of abstraction thanthe business rules and managed entities (e.g., network commands). Thisenables policies to be built to proactively monitor network services andadjust, for example, the corresponding configurations of managedentities to ensure that the business processes of a particular serviceis met by the devices providing those services. The term “service”refers generally to a functionality of a network that can be provisionedfor a customer, such as a VPN service. The term “policy” refersgenerally to a set of rules that are used to manage and control thechanging and/or maintaining of the state of one or more managed entitiesas objects.

Referring now to the drawings, where like or similar elements aredesignated with identical reference numerals throughout the severalviews. In particular, FIG. 2 illustrates an exemplary representation ofa managed entity according to one embodiment of the present invention.For example, managed entity 202 of representation 200 can be defined asan object-oriented representation of any entity that can be managed in anetwork system. As an example of a managed entity, FIG. 3 illustrates arouter as managed entity 202 of FIG. 2.

According to one embodiment, an exemplary information model with whichmanaged entity 202 relates is an object-oriented information model. Thisinformation model uses a set of object-oriented classes andrelationships to describe one or more of the following: the physicalcomposition of devices, the logical characteristics of devices, a set ofmappings between a logical feature and each of the physical entities(e.g., devices) that supports the logical feature, a set of mappingsbetween a logical feature and the specific commands that a particulardevice employs to support that feature, and like information and/or datafor managing and configuring a network in accordance with the presentinvention. Note in particular that such representations are inherentlyextensible, as they can be constructed using separate managed entitiesto represent each of the above sets of functionality.

In one embodiment, each managed entity can be represented by a datamodel to represent all or some information that describes that managedentity. In another embodiment, a larger data model can represent manymanaged entities. In yet another embodiment, more or fewer of theforegoing features can constitute a managed entity in accordance withthe present invention.

Managed entity 202 of FIG. 2 is shown as being represented by eitherphysical objects 204 or logical objects 206, or both. Physical objects204 can include one or more physical objects “PO₁,” “PO₂,” etc. todescribe the physical entities, and logical characteristics 206 caninclude one or more logical objects “LO₁,” “LO₂,” etc. that describe thelogical entities of managed entity 202. Alternatively, physical objects204 and/or logical objects 206 can be related to no objects to describeeither physical or logical entities. Although representation 200 isshown as hierarchical tree structure comprising nodes havingparent-child relationships, representation 200 can be represented aslayered model of layered class hierarchies. The layered class ofhierarchies enables an information model to be used to representappropriate amounts of detail for one or more of the different aspectsof an object representing a managed entity. The different hierarchies ofrepresentation 200 and relationships among the elements ofrepresentation 200 can be related with associations, aggregations,compositions and the like. One having ordinary skill in the art willappreciate that FIG. 2 is but an example of how the elementsconstituting a managed entity can be described and related. That is, theelements and relationships depicted in FIG. 2 are exemplary and are notintended to be inclusive (e.g., interrelationships can exist betweensibling nodes of the same managed entity or among nodes of other managedentities). For example, there can be a number more categories ofphysical objects and relationships constituting managed entity 202 thanthose shown in FIG. 2.

Physical objects 204 can describe the physical composition of managedentity 202 as a set of object-oriented classes. As shown in FIG. 2,physical objects 204 can include one or more physical objects “PO₁,”“PO₂,” etc. to describe the physical entities required by managed entity202 to accomplish a specific management task. Further, each of physicalobjects 204 can be described by additional managed objects that arerelated to each other, where these managed objects can be associatedwith physical and/or logical entities. A particular type of relationshipbetween managed objects can be represented as a composition 208.

For example, consider a line card having a physical port, where thatport is related to an IP address. Then, the line card can be representedby object “PO₂,” the physical port can be represented by “object A” 209(i.e., as a physical object), and the IP address can be represented by“object B” 211 (i.e., as a logical object). The relationships betweenthese objects can be described as composition(s) 208. In particular,“CMP₁” and “CMP₂” describe respectively, as compositions, therelationship between PO₂ and object A and the relationship betweenobject A and object B. In this example, CMP₁ relates the physical portto the line card and CMP₂ relates the IP address to the physical port.Thus, composition(s) 208 enable the lifecycles of the physical port andIP address to be represented as a function of the life cycle of the linecard (i.e., the physical port cannot exist without its parent line card;if the card is removed from the network, the associated physical portand its associated IP address “disappear,” or are disassociated with thenetwork).

Thus, by using relationships, such as compositions 208 and others notshown in FIG. 2, a detailed understanding of the physical structure ofmanaged entity 202 can be developed for a number of network-relatedtasks, such as managing physical inventory. For example, the managementof physical inventory can be facilitated by a “view” of the physicalinventory, where a view, as described herein, refers generally tocollated entities that are applicable for understanding a particularperspective. One method for managing physical inventory (i.e., managing“stranded assets”) is described in U.S. patent application Ser. No.10/617,420, entitled Repository-Independent System and Method for AssetManagement and Reconciliation, filed Jul. 10, 2003 and assigned to anassignee in common with the subject application.

In addition, each of physical objects 204 can be associated with one ormore equivalent physical capability mappings 214 (“EPC₁,” “EPC₂,” etc.)for determining equivalent physical compositions for constitutingmanaged entity 202. In particular, these mappings define equivalentphysical capabilities between different devices for relating thedifferent hardware capabilities of each device to each other. Withequivalent physical capabilities associated with managed entity 202,different devices that are required to work together can be identifiedto implement a common function of managed entity 202 regardless ofwhether the common functionality requires different hardware. With thesesimilar physical capabilities identified and represented independent ofany specific vendor, equivalent physical capability mappings 214 canprevent physical mismatches and are useful in programming (e.g.,establishing) a service that spans multiple physical devices. Forexample, a given line card manufactured by vendor “A” may have eightphysical ports of a given type (e.g., “Ethernet”), whereas a differentline card manufactured by vendor “B” may only have four physical portsof that same type (e.g., Ethernet). That is, vendor B's cards only havehalf the number of ports that vendor A's cards have. Thus, any twodevices would have the equivalent physical capabilities if using either“L” number of vendor A line cards or “2*L” number of vendor B'sequivalent line cards.

Logical objects 206 can describe the logical characteristics of managedentity 202 as a set of object-oriented classes. As shown in FIG. 2,logical objects 206 can include one or more logical objects “LO₁,”“LO₂,” etc. to describe the logical entities required by managed entity202 to accomplish a specific network-related task (e.g., managing andprovisioning). Further, each of logical objects 206 can be described byits logical characteristics 210, such as “CHR₁,” “CHR₂,” etc., thatconstitutes the logical entities of managed entity 202, which provide avendor independent view of logical device capabilities. Using logicalcharacteristics 210, a detailed understanding of the functionality ofmanaged entity 202 can be used for a number of network-related tasks,such as modeling logical features (e.g., interfaces, software, etc.) ofor relating to a device. By modeling the functions that a network deviceprovides, then that device can easily be identified and implemented toestablish a service that requires support by that device and itsfunctionality. For example, if a device is required to be used toimplement a virtual private network (“VPN”) and the device's logicalentities (e.g., features and functionalities) are modeled to provide afunction or feature of the VPN, then the modeled role of the device inimplementing the VPN can be selected and provisioned to enable thatparticular service.

In addition, each of logical objects 206 can be associated with one ormore equivalent logical capability mappings 218 (“ELC₁,” “ELC₂,” etc.)for determining equivalent logical capabilities or features forconstituting managed entity 202. These mappings define how differentlogical capabilities of each network device relate to each otherindependent of any particular vendor. In particular, these mappings candefine equivalent logical capabilities (i.e., functionalities) betweendifferent devices as well as equivalent logical capabilities betweendifferent features of different device implementations. With equivalentlogical capabilities associated with managed 202, different devices thatare required to work together can be identified to implement a commonfunction of managed entity 202 regardless of whether the commonfunctionality requires, for example, different software capabilities.Some examples of logical capabilities that can be modeled are differentcommands, differently supported protocols, different operating systems,and other like logical dissimilarities.

Hardware linkage mappings 216 include a set of mappings that definelinkages of logical features associated with one of logical objects 206to physical entities (e.g., hardware) to support those logical features.These mappings enable the identification of hardware to implement aparticular logical feature. For example, hardware linkage mappings 216can be used to determine whether hardware exists to support a desiredlogical feature, whether any physical capacity is available for use tosupport enabling an implemented service, whether a particular featurecan be run at a given line rate, and other like information related tophysical entities providing logical features. In other words, hardwarelinkage mappings 216 enable the logical capabilities of a device to bebound to existing physical hardware for implementing a commonfunctionality using specifically identified physical hardware, as anexample.

Vendor-specific commands mappings 212 include a set of mappings thatdefine relationships among different logical features and thevendor-specific commands required to implement that logical feature. Inparticular, the same command can be mapped to a different combination ofvendor-specific features (e.g., commands or syntaxes). Consider anetwork formed using heterogeneous devices (i.e., different devices fromdifferent vendors), each of which can be employed to realize high-levelconcepts such as the ability to run a particular protocol, to forwardtraffic, and the like, where these abilities are generally implementedusing different commands and/or features. In accordance with at leastone embodiment of the present invention, commands of different devicescan be abstracted as a set of capabilities that can either be bound toavailable hardware, or can be mapped to higher-level services, or both.This enables a scalable network management system for provisioningend-to-end services independent of any specific vendor.

FIG. 3 is an exemplary managed entity representing a router. Accordingto an embodiment of the present invention, a router can be representedby a set of data models that represent physical and logical deviceinformation that each describes one or more managed entities. Ingeneral, each data model can represent all or some information thatdescribes a particular managed entity. For example, a router can beassociated with physical information (e.g., the set of line cards thatare installed in the router) as well as logical information (e.g.,protocols that are running on each of its interfaces). Other exemplarylogical information can include protocol information, serviceinformation (e.g., connectivity using a VPN), statistical information(e.g., data describing how well a service is running), ownershipinformation (e.g., who owns the device, who is responsible for changingthe device), security information, and other like information.

As shown, managed entity representation 300 describes router 302including physical objects 304 and logical objects 306. Here, physicalobjects 304 include two line cards as objects 350 (“Linecard₁”) and 352(“Linecard₂”). For objects 350 and 352, the logical connectivity ofrouter 302 is respectively represented by IP 354 and SONET 356, both ofwhich have their respective relationships to line cards 350 and 352described as composition(s) 308. Both IP 354 and SONET 356 can bephysical ports 309, as an example, and are represented as physicalobjects. In this instance IP 354 is a line card for providing IPcapabilities and SONET 356 is a line card for providing SONETcapabilities. As shown, Linecard₂ 352 is associated with anotherequivalent physical capability 314 and includes as mapping 358 toanother line card (“SONET connection”) for providing SONET capabilities.Notably, line cards 350 and 352 each can also be represented as managedentity 202 of FIG. 2 for providing a common representation in avendor-independent format.

Logical objects 306 can include a number of logical capabilities, suchas certain functionalities (e.g., firewall-like functions), features(e.g., protocols), etc. As shown, logical objects 306 include logicalobjects “protocols” 360, “firewall” 362, and “commands” 364. In thisinstance, protocol 360 includes logical characteristics 310 as “OPSF”364 and “BGP4” 366 as protocols, or logical features, of router 302.Firewall 362 is associated with an equivalent logical capability mapping318, which maps to a “packet-filtering” 368 functionality as a similarlogical capability that router 302 can perform. Thus, router 302 can beidentified as being able to provide firewall functionality, if a service(e.g., VPN) is to be implemented with that function. Notably, protocols360, firewall 362, and commands 364 each can also be represented asmanaged entity 202 of FIG. 2 for providing a common representation in avendor-independent format.

Router 302 is also shown to be associated with a certain set of commandsas commands object 364. Here, CLI set one 370 can include a variety ofmappings for implementing vendor-specific commands. Hence, router 302can be managed and/or provisioned with a normalized set of commandsusing these mappings. FIG. 3 is only an exemplary representation;additional logical and physical capabilities can be further representedin FIG. 3, such as which of the line cards have available ports (i.e.,via hardware linkage mapping 216 of FIG. 2), which of those ports arecongested as described by statistical information, and other likecapabilities. One having ordinary skill in the art should appreciatethat the physical and/or logical capabilities of router 302 can berepresented as one or more sets of managed entities 202 of FIG. 2.

An exemplary information model of the present invention uses commonrepresentations of various managed entities, such as shown in FIGS. 2and 3 to normalize physical and logical entities of a network byperforming mapping translations from current programming models tovendor-independent data models (i.e., independent of implementationtechnology). The information model is used to define how differentcharacteristics of the managed entities should be mapped as well as whatform it should take in the vendor-independent data models. To performmapping translations in accordance with an embodiment of the presentinvention, there are “n” sets of mappings from the information model toa vendor-independent data model stored in one or more repositories (in aform appropriate to each of the repositories). The “n” sets of mappingsare the number of relevant data models, where each mapping to a uniquerepository is due to at least different access protocols, storagestructures, and/or other characteristics that differentiate itsimplementation. In at least one embodiment, one repository is adirectory and another repository is a relational database, or any otherknown database.

Optionally, there may be additional “m” sets of mappings, each of whichresults in a mapping of a data model (e.g., stored in a repository) to avendor-specific (i.e., optimized) implementation, such as one or moredifferent “m” number implementation for each vendor-specific product.Each of the “m” sets of mappings is used because different vendors andphysical entities implement the same features (e.g., software, commands,etc.) differently as well as the functions performed. As such, a singlemapping can exist from an information model to a data model stored in aspecialized form for a given type of repository. But many mappings mayexist to map from the specialized form of the data model to implementdifferent vendor's commercial products of the repository.

For example, different implementations of different types ofrepositories generally have very different functional differencesbetween them, such as the case with directory servers and relationaldatabases. In each case, there is an underlying standard (e.g., “LDAP”and “SQL”) that serves as an access protocol, which governs howinformation is stored to and retrieved from the repository. Yet, in eachcase, vendors generally have implemented part, but not all, of astandard. In some cases, other vendors have added their own extensions,or alternatively, have not implemented everything in the standard. Thus,each case requires one or more mappings from repositories implementing astandard to the vendor-specific implementation in order to leverage thevendor-specific implementation.

FIG. 4 illustrates one method of performing mapping translations usingan exemplary information model in accordance with one embodiment of thepresent invention. Although FIG. 4 depicts only one information model406, other embodiments of the present invention can include multipleinformation models 406. In embodiments using multiple informationmodels, a method similarly represented in FIG. 4 can ensure that eachmanaged entity is represented in the same, common manner among all ofthe multiple information models by using a data dictionary to validatedata coherency.

As shown in FIG. 4, characteristics of different devices (i.e.,physically and/or logically), such as one or more programming models,are first incorporated at 450 into a common representation ofinformation model 406. In this example, information from sources CLI 402and 404, and from MIBs and PIBs 406, which use SNMP, are synthesizedfrom different programming models into a common representationassociated with relevant physical and logical entities.

Exemplary information model 406 at 452 abstracts the data used byvendor-specific programming models into vendor-independent (andtechnology-independent) data models by, for example, using definitionsfor the managed entities' devices and relationships (i.e., physical andlogical). Information model 406 is a federated model and therefore isused to process information from any source necessary for practicing thepresent invention. Notably, information model 406 contains definesconcepts, such as CLI, MIBs, and the like, as well as other means ofmanaging devices in its structure. For example, information model 406provides common information for defining a higher-level abstractionlayer. A higher-level abstraction layer can be used to incorporate thedata required by different vendor-specific programming models, and torelate these data to different business, system, and implementationentities, which in turn are used to represent the managed environment.This provides for a common definition for attributes, methods, andrelationships of entities to be managed. It also provides a set ofsynonyms, source of material, and other essential information so thatdesigners can better understand and use the model. Information model 406can also include a set of business and system models for specificknowledge domains (e.g., service, resource, customer, etc.), where theconcept of knowledge domains is discussed below.

FIG. 5A is an exemplary information model represented as a set oflayered information sub-models according to one embodiment of thepresent invention. Each layer of information model 500 includes a set ofobjects that are common to that layer, where each layer represents adifferent level of abstraction. Further, each layer can be a way oforganizing information such that the information can be classified asknowledge (e.g., with respect to a particular knowledge domain).Moreover, each of the layers is related to each other using appropriaterelationships (e.g., associations, aggregations, compositions, and otherlike relationships). As an example, entities associated with lowerlayers of information model 500 can “inherit” characteristics ofentities defined in its higher layers. As such, different programmingmodels of the same device (or device feature) can be integrated and/orcorrelated with each other. Hence, different features that are prone tochange (relative to other features associated with a network) can beisolated from each other. This allows specific feature changes in adevice model (e.g., software revisions, as they are generally prone tochange) to be easily accommodated by the network and by the businessprocesses, depending upon those feature changes. And it also enablesfeatures that are prone to change to be separately modeled.

As shown in FIG. 5A, layer 502 includes one or more objects that, forexample, are defined in a business view of the managed environment. Thebusiness view includes a set of business-oriented representations (e.g.,using objects) for implementing business processes, guidelines andgoals. These representations are generally designed for businessentities, such as customers, service, service level agreements (SLA), orother users that need not be exposed to the system level abstraction.For example, a customer is not particularly interested in learning whatsystem-level requirements are necessary to provide a service, such asthe settings of a particular internal gateway protocol (“IGP”) forrouting or the protocols for establishing a VPN service, at the businesslevel. Layer 502 is related via relationship 508 to layer 504.

In one embodiment, relationship 508 is a mapping (or a translation) fromone business-oriented representation to two system-orientedrepresentations (i.e., two system-level objects) having a relationship512 between these two system-level objects.

In this instance, layer 504 includes two objects that, for example,provide a system view. The System view includes a set of system-orientedrepresentation (e.g., objects associated with system view 554) of alevel of detail for managing the business processes, such as what typeof VPN is necessary for implementation. These representations aregenerally designed for users that need not be exposed to thetechnology-specific aspects of a system-level abstraction. Inparticular, abstractions at this level and translations with this levelare generic in nature and avoid choosing a specific technology such asDifferentiated Services (“DiffServ”) or a specific implementation (e.g.,IOS CLI over Telnet).

Further to the example shown in FIG. 5A, relationship 510 is a mappingfrom the system-oriented representations to four implementation-orientedrepresentations (i.e., four system-level objects) interrelated byrelationships 514 among the four implementation-level objects. Here,layer 506 includes four objects. As an example, these objects caninclude administrator-related representations (i.e., associated withadministrator view 556) used to map to technology-specificimplementations from the system level. As another example, these objectscan include device-related representations (i.e., associated with deviceview 558) for mapping a selected implementation into a form that isappropriate for a specific type of device. In addition, these objectscan include instance-related representations (i.e. associated withinstance view 560) to map that specific type of device to aconfiguration that takes into account the specific software versions,memory configuration; and other factors ancillary to the functionalityof the device.

As shown in FIG. 5A, each of the different “views” 550 is associatedwith a different level of abstraction. Views 550 can describe one ormore policies that can be applied to the information model layers todetermine the specificities of translating business needs of anorganization into a particular device configuration. And the applicationof a specific set of policies is tailored to the needs of differentdomains (i.e., “knowledge domains”) of users as well as services anddevices, for example. These sets of policies for each of views 550 bindthe different views, such as the business-oriented, system-oriented, andimplementation-oriented views, to the different levels of theinformation model 500. In one embodiment, views 550 (i.e., business view552, system view 554, administrator view 556, device view 558, instanceview 560, or other views, if applicable) each represent a differentknowledge domain. In this case, each of the knowledge domains can befurther subdivided. For example, the business view can include“product-specific” views, “customer-specific” views,“marketing/sales-specific” views, and the like. In other embodiments,views 550 can represent other entities, which can be described whereview 552 is a first layer, view 554 is a second layer, view 556 is athird layer, view 558 is a fourth layer, and view 560 is a fifth layer.

As described herein, a “knowledge domain” refers to a classification ofknowledge, such as the knowledge for describing a device, a product, aservice or the like. Knowledge domains can be formed to reflect howinformation is classified and organized. Knowledge domains can be usedto split apart a large number of management entities for organizing theminto related sets of entities. They also serve to define how themodeling activity is performed. For example, by defining separateknowledge domains for a “product” and a “service,” specialists in eacharea can work on each area independently as well as concurrently, and ina manner adapted to each of the specialists' area of expertise. Forexample, a knowledge domain can represent one or more sets of entitiesthat pertain to a particular area (e.g., service or product). Behavioris represented, in part, by relating different entities to each other.These relationships can be within a specific knowledge domain or amongentities in multiple knowledge domains. Although it is generally commonto relate entities within a specific knowledge domain to each other(because there is already some inherent relationship between entities ofa particular domain), entities of one knowledge domain can also berelated to other entities in other knowledge domains.

FIG. 5B is another representation of the exemplary information model ofFIG. 5A, which is shown as a layered, next generation directory enablednetwork (“DEN-ng”) information model according to a specific embodimentof the present invention. Exemplary information model 570 includes acore framework 572 and knowledge domains 574. Core framework 572 is thehighest layer in the DEN-ng information model and contains high-levelentities and relationships that enable more specific domain models 574to be integrated into a single cohesive model. As shown in FIG. 5B,knowledge domains 574 include product model 576, location model 578,party model 580, event model 582, interaction model 584, serviceframework 588, resource framework 586, and policy framework 590. Each ofthese models have multiple layers that define multiple levels ofabstraction, such as shown in FIG. 5A, that is used to organizeinformation in a given knowledge domain. Further to this example,service framework 588, resource framework 586, and policy framework 590can provide additional abstractions for representing concepts applicableto the entities in these domains. That is, service framework 588 caninclude a physical, a logical and a network model, resource framework586 can include a resource-facing and a customer-facing serviceframework, and policy framework 590 can include a behavioral and astructural framework. It should be again noted that FIGS. 5A and 5B areexemplary in nature, and should not be construed to be limiting in anyway.

Referring back to FIG. 4, after a common representation is defined byinformation model 406, that representation can be translated into one ormore data models. Data models can be built by translating theinformation describing one or more managed entities (i.e., objects)represented in an information model to one or more managed entities(i.e., objects) represented in a specific data model. These translationscan be built by, for example, developing a set of rules that translateinformation at one level of abstraction (i.e., one layer) to data at adifferent level of abstraction (i.e., at another layer, such as a higherlayer). In this example, FIG. 4 shows two such translations; onetranslation to one or more data models stored in directory 408 andanother translation to one or more data models in database 410.

Although directory 408 and database 410 are shown as repositories,additional types of repositories are within the scope of the presentinvention. For example, two or more additional repositories, that couldtake the place of either directory 408 or database 410, generally havedifferent capabilities, such as different access protocols and differentways of storing data. These different repositories can each require oneor more data models, where each data model contains at least theinformation mapped from information model 406 into a vendor-independentform that represents standards-based ways of storing and retrieving datafrom each type of repository. While standards exist for representing,querying, and manipulating data in different repositories, vendorimplementations using that data are non-standard. Repository standardscan be referred to as Repository Data Specifications (“RDS”).Specifically, vendors routinely add functionality to a repository beyondthe requirements of an RDS, or, alternatively, vendors do not implementall of the functions specified by an RDS. Further, multiple vendorsimplement the same function in their devices in different ways. For atleast these reasons, a preliminary vendor-independent repository modelis required to serve as a normalization layer between the data in theform of an information model and the information that will be stored inand/or retrieved from a repository (which usually is in the form of avendor-independent data model).

The mapping of vendor-independent data model 454 includes a set ofmappings that transform data represented in a common representation ininformation model 406 to a form that can be implemented in a particulartype of repository, such as in database 410. Thus, an object that isrepresented in the information model may be represented differently ineach data model in each different repository. See FIG. 7 and thediscussion relating thereto, as an example. This is because each datamodel has a specific set of capabilities and restrictions inrepresenting information, which can include one or more accessprotocol(s) being used.

Examples of a multiple access protocols used on a repository are SQL92,vendor-specific SQL, and/or ODBC (as used with RDBMSs, or relationaldatabase management systems). Other data model capabilities can includethe manner in which data is stored and organized, how relationshipsbetween objects are implemented, and whether a given type of repositoryhas specific facilities, such as for implementing metadata and behavioras specified in the information model. In one embodiment, these andother repository-dependent features form a “mapping vector” thatprescribes how data is to be represented in a particular informationmodel. This in effect restricts what subset data from the commoninformation model can be represented, and determine how those data arerepresented. For example, directories such as directory 408 of FIG. 4have much more limited forms of locating information than do relationaldatabases such as database 410. Furthermore, directories tend to usedifferent protocols than do relational databases. This means that someinformation that can be easily represented in a RDBMS cannot be easily(if at all) represented in a directory. The mapping vector serves todefine how information in a data model can be translated to a form thatcan be stored and retrieved using the native facilities of a particulartype of repository.

After a common vendor-independent repository data model is built at 454using information model 406, then the appropriate portions of thatcommon information can be transformed into a repository-specificimplementation at 456. Note that at 454, the information modeltransforms the data into a form that is suitable for implementationusing a particular type of data model. This transformation isvendor-independent, and therefore generic-like, in nature. Therefore,the transformed data can be viewed as being in a “repository-standard”form of the data. But most applications require an “optimized”implementation, rather than the generic implementation. An optimizedimplementation can refer to a further mapping of vendor-dependentfeatures and the like at 456.

Optionally, at 456 a different “mapping vector” can be applied to therepository-standard form of the data stored, for example, in data modelof database 410 to again transform the repository-standard (butvendor-independent) form of the data into a vendor-specificimplementation of that repository. For example, consider that avendor-independent data model of database 410 is mapped to twovendor-dependent data models, as shown as “data model of vendor 1” 412and “data model of vendor 2” 414. Each of these two data models can bein specific repositories for providing an optimized functionality.

For example, consider the modeling of a device interface as a data modelin database 410. This interface may be described using a number ofdifferent programming models, such as using CLI rather than using SNMP.But suppose determining that a particular piece of information, such asthe number of packets dropped per unit of time, is desired. Informationmodel 500 and 570 of FIGS. 5A and 5B, respectively, can represent thisinformation in a repository-independent form. However, the acquisitionof the piece of information, in code, requires selecting a particulartype of repository. Because the frequency of change of this attribute isvery high (relative to other entities), direct storage in certain typesof repositories, such as a directory, is suboptimal. Consequently, arepository such as database 410 is more suitable for storing suchinformation. As another example, consider the modeling of a user as adata model in database 410. Suppose that this entity has an attributethat contains the “Employee ID” of the user. This attribute likely doesnot change frequently during the time of employment of the user, andthus is suitable for storing a relevant data model in directory 408.

In another embodiment of the present invention, an exemplary informationmodel can be further configured to facilitate collecting, correlating,and integrating different types of information describing one or morefeatures of a device from different sources. Such an exemplaryinformation model can be configured to be structured to performfunctionalities of other embodiments, but also can relate data in manydiverse data formats, which are typically supplied from differentinformation sources in a normalized fashion. Normally, different typesof statistics and performance information are gathered by differentmeans without a normalized technique for correlating that informationfrom each of the different devices.

For example, a MIB variable defining the packet drop rate of aninterface can be generally obtained using traditional SNMP pollingmechanisms. Further, consider that statistic data is generated to definethe current number of active users. If a network operator desires tofine-tune a network to ensure that each of the active users receives theservice for which it has contracted (e.g., without violating aparticular SLA), then the network operator requires information thatrepresents the actual, current service level for comparison with thecontracted levels of the SLA. As the rate of packet loss can beindicative of an upcoming SLA violation, a network operation will seekto normalize the diversely formatted data, which are being supplied fromdifferent information sources, for determining how best to provideguaranteed service levels over differing rates of packet loss andnumbers of active users. The exemplary information model of at leastthis embodiment can be employed to assist in management of networkperformance such as described above.

FIG. 6 illustrates a system for using an exemplary information model tofacilitate the collection, correlation, and integration of differenttypes of information describing one or more features of a device fromdifferent sources. in this example, system 600 includes one to “n”information sources 602. Information sources 602 are different deviceshaving different command syntaxes, different programming models, and/ordifferent functionalities, such as information sources CLI 402 and 404and from MIBs and PIBs 406 of FIG. 4. System 600 also includes a commonmedia layer 606 coupled to each of data model mappings 608, which can beequivalent to data models stored in repositories, such as database 410for FIG. 4. Common media layer 606 is coupled to receive via rulesengine 610 model mapping rules from database 612. Note that “n” and “m”of FIG. 6 are used to describe features in connection with this figureonly; they do not relate to “n” and “m” as defined in other figuresdescribed herein.

Common mediation layer 606 operates to preserve the semantics ofreceived information (e.g., serves as a “glue” layer), but transformsthe received information into a common representation and format forintegration with other common information in the exemplary informationmodel. Through the use of common mediation layer 606, additional partsof the information model need only be specified, or built, on an“as-needed” basis, thus avoiding building a complete information modelthat generally contains many or all pre-defined entity (i.e., physicaland/or logical) and behavior (i.e., functionality) for mapping to any ofthe specific data models 608. This enables portions of an overallnetwork architecture to be designed without having to wait for theentire exemplary information model to be completed before it isavailable for use.

In operation, information (e.g., performance information from MIBs)received from information sources 602 is compared to the informationmodel, which functions in this example as a data dictionary. Then,common mediation layer 606 transforms the received information into acommon representation and assigns the information to an appropriateentity (or entities) using the data dictionary. The assignment of theinformation is performed in accordance with a set of mapping rules indatabase 612. Rules engine 610 uses these mapping rules for comparingthe received information to data describing managed entities representedby the information model, and then selecting a suitable entity (orentities) for the assignment.

Optionally, system 600 further includes “m” number of adaptation layers(e.g., for performing syntactic adaptation), where adaptation layers 604are configured to optimize the interfacing of information sources 602 tocommon mediation layer 606. Here, one or more of information sources 602are coupled to one of adaptation layers 604, where at least one ofadaptation layers 604 serves as a bridge to connect sets of informationsources 602 to common mediation layer 606. Adaptation layers 604 enablesimilar capabilities, behavior and characteristics of physical and/orlogical entities to be grouped together so that the same process can beused to translate the information, as a group, into common mediationlayer 606 for further processing. For example, consider two differentprivate MIBs of information sources 602, such as “information source 1”and “information source 2,” that are used to describe certain interfacestatistics for two different routers. If the router features are definedusing common capabilities, then these interfaces statistics can be foundto be the same. Thus, adaptation layer 620 (“adaptation layer 1”) can beused to present each router's statistics to common mediation layer 606.

In one embodiment, each of the elements of system 600 is aninterconnected module including software, hardware, or a combinationthereof. In another embodiment, system 600 is implemented as middlewaresuch that a new “instance model” can be generated based on the receivedinformation according to the knowledge contained in the informationmodel. As an example, the instance model reflects the current state ofmanaged entities for immediate use in a network.

FIG. 7 is an exemplary model for representing a user according to oneembodiment of the present invention. In this instance, model 700 isindependent of a repository and does not define how to enable thevendor-specific implementations. Rather, model 700 is a guide forvendor-independent implementation. Note that classes 706 of FIG. 7 areshown as an example only, and are not intended to be limiting. Model 700can serve to represent a Party 714 as a container that can holdPartyRoles 712. Model 700 can also serve to represent Party 714 andPartyRole 712 as separate objects in model portions 704 and 702,respectively, which are related by an aggregation, for example, thatconnects them. In another embodiment, model 700 represents all or aportion of party model 580 of FIG. 5B.

But the actual implementation may vary depending how model 700 isviewed. That is, if Party 714 is viewed as a container that can holdPartyRoles 712, the user can be better represented in a directory, suchas directory 408 of FIG. 4. This is because the directory excels atimplementing containment relationships. By contrast, if model 700 isviewed as representing Party 714 and PartyRole 712 as separate objects,then is easier to implement model portions 704 and 702 in an RDBMS,since its strength is to be able to relate diverse information to eachother. Therefore, although the directory and RDBMS implementations ofmodel 700 are physically different, they can be related to each otherbecause they are derived from the same information model. That is, ifmodel 700 can be represented by information model 460 of FIG. 4, then afirst data model describing Party 714 as a container holding PartyRoles712 is preferably stored in directory 408, whereas a second data modeldescribing Party 714 and PartyRole 712 as separate objects is preferablystored in database 410. Note that FIG. 7 represents a mere example oftransforming data in vendor-independent form from an information modelto the one or more repositories.

An embodiment of the present invention relates to a computer storageproduct with a computer-readable medium having computer code thereon forperforming various computer-implemented operations. The media andcomputer code may be those specially designed and constructed for thepurposes of the present invention, or they may be of the kind well knownand available to those having skill in the computer software arts.Examples of computer-readable media include, but are not limited to:magnetic media such as hard disks, floppy disks, and magnetic tape;optical media such as CD-ROMs and holographic devices; magneto-opticalmedia such as floptical disks; and hardware devices that are speciallyconfigured to store and execute program code, such asapplication-specific integrated circuits (“ASICs”), programmable logicdevices (“PLDs”) and ROM and RAM devices. Examples of computer codeinclude machine code, such as produced by a compiler, and filescontaining higher-level code that are executed by a computer using aninterpreter. For example, an embodiment of the invention may beimplemented using XML, Java, C++, or other object-oriented programminglanguage and development tools. Another embodiment of the invention maybe implemented in hardwired circuitry in place of, or in combinationwith, machine-executable software instructions.

In conclusion, various illustrative embodiments of the inventionprovide, among other things, methods and systems for managing a computernetwork and obtaining information from different devices in a computernetwork. Those skilled in the art can readily recognize that numerousvariations and substitutions may be made in the invention, its use, andits configuration to achieve substantially the same results as achievedby the embodiments described herein. For example, other access rights,such as “open,” “execute,” “move,” etc., and other actions, such assynchronization of files and/or devices, one or more instructions of acommand set, etc., can be used to supplement the enforcement of thesecurity set definitions described herein. Accordingly, there is nointention to limit the invention to the disclosed exemplary forms. Manyvariations, modifications, and alternative constructions fall within thescope and spirit of the disclosed invention as expressed in the claims.

1-9. (canceled)
 10. A computerized method for obtaining information fromdifferent devices in a computer network, the method comprising:receiving data representing the information from each of the differentdevices, wherein the data is in a specific form relating to each of thedifferent devices; assigning the data from each of the different devicesto one or more entities as defined by an information model; and groupingthe data from each of the different devices using an adaptation layerbefore assigning the data from that device to one or more entities. 11.The method of claim 10, wherein assigning the data further comprises:preserving a semantic of the received data; comparing received dataagainst one or more managed entities; and transforming the data into acommon representation.
 12. The method of claim 11, further comprisingusing the common representation of the data to monitor the performanceof the network.
 13. The method of claim 11, wherein transforming thedata into a common representation is performed by a mediation layer. 14.(canceled)
 15. A system for obtaining information from different devicesin a computer network, the system comprising: a processor; a memorycontaining a plurality of program instructions configured to cause theprocessor to: receive data representing the information from each of thedifferent devices, wherein the data is in a specific form relating toeach of the different devices; assign the data from each of thedifferent devices to one or more entities as defined by an informationmodel; and group the data from each of the different devices using anadaptation layer before assigning the data from that device to one ormore entities.
 16. The method of claim 10, wherein a set of mappingrules are used to assign the data from each of the different devices tothe one or more entities and wherein the mapping rules control changesmade to a state of each of the entities in the one or more entities. 17.The method of claim 11, wherein statistics associated with each of thedifferent devices are provided by the adaption layer prior to the databeing transformed into the common representation.
 18. The method ofclaim 17, wherein the statistics are interface statistics indicating atleast one of capabilities, behavior, or characteristics associated witheach of the different devices.
 19. The system of claim 15, wherein theinstructions to assign the data further cause the processor to: preservea semantic of the received data; compare received data against one ormore managed entities; and transform the data into a commonrepresentation.
 20. The system of claim 19, wherein the instructionsfurther cause the processor to: use the common representation of thedata to monitor the performance of the network.
 21. The system of claim19, wherein transforming the data into a common representation isperformed by a mediation layer.
 22. The system of claim 15, wherein aset of mapping rules are used to assign the data from each of thedifferent devices to the one or more entities and wherein the mappingrules control changes made to a state of each of the entities in the oneor more entities.
 23. The system of claim 19, wherein statisticsassociated with each of the different devices are provided by theadaption layer prior to the data being transformed into the commonrepresentation.
 24. The system of claim 23, wherein the statistics areinterface statistics indicating at least one of capabilities, behavior,or characteristics associated with each of the different devices.
 25. Acomputer storage product comprising a computer readable medium having acomputer code stored therein, wherein the computer code, when executedon a computing device, causes the computing device to: receive datarepresenting the information from each of the different devices, whereinthe data is in a specific form relating to each of the differentdevices; assign the data from each of the different devices to one ormore entities as defined by an information model; and group the datafrom each of the different devices using an adaptation layer beforeassigning the data from that device to one or more entities.
 26. Thecomputer storage product of claim 25, wherein the computer code toassign the data further causes the computing device to: preserve asemantic of the received data; compare received data against one or moremanaged entities; and transform the data into a common representation.27. The computer storage product of claim 26, wherein the computer codefurther causes the computing device to: use the common representation ofthe data to monitor the performance of the network.
 28. The computerstorage product of claim 26, wherein transforming the data into a commonrepresentation is performed by a mediation layer.
 29. The computerstorage product of claim 25, wherein a set of mapping rules are used toassign the data from each of the different devices to the one or moreentities and wherein the mapping rules control changes made to a stateof each of the entities in the one or more entities.
 30. The computerstorage product of claim 26, wherein statistics associated with each ofthe different devices are provided by the adaption layer prior to thedata being transformed into the common representation and wherein thestatistics are interface statistics indicating at least one ofcapabilities, behavior, or characteristics associated with each of thedifferent devices.